Among the Resources in this module is the Rutherford (2008) article Standardized Nursing Language: What Does It Mean for Nursing Practice? In this article, the author recounts a visit to a local hospital to view the recent implementation of a new coding system.

During the visit, one of the nurses commented to her, “We document our care using standardized nursing languages but we don’t fully understand why we do” (Rutherford, 2008, para. 1).

How would you respond to a comment such as this one?

To Prepare:

  • Review the concepts of informatics as presented in the Resources, particularly Rutherford, M. (2008) Standardized Nursing Language: What Does It Mean for Nursing Practice?
  • Reflect on the role of a nurse leader as a knowledge worker.
  • Consider how knowledge may be informed by data that is collected/accessed.

The Assignment:

In a 2- to 3-page paper, address the following:

  • Explain how you would inform this nurse (and others) of the importance of standardized nursing terminologies.
  • Describe the benefits and challenges of implementing standardized nursing terminologies in nursing practice. Be specific and provide examples.
  • Be sure to support your paper with peer-reviewed research on standardized nursing terminologies that you consulted from the Walden Library.

!

Evidence of Progress in Making Nursing Practice Visible Using Standardized
Nursing Data: a Systematic Review

Tamara G. R. Macieira, BSN, PhD student1, Madison B. Smith, BSN, RN, PhD student1
Nicolle Davis, BSN, RN, SCRN, PhD student1, Yingwei Yao, PhD1, Diana J. Wilkie, PhD,

RN, FAAN1, Karen Dunn Lopez, PhD, MPH2, Gail Keenan, PhD, RN, FAAN1
1University of Florida, Florida; 2University of Illinois at Chicago, Illinois

Abstract

Nursing care documentation in electronic health records (EHRs) with standardized nursing terminologies (SNTs) can
facilitate nursing’s participation in big data science that involves combining and analyzing multiple sources of data.
Before merging SNTs data with other sources, it is important to understand how such data are being used and analyzed
to support nursing practice. The main purpose of this systematic review was to identify studies using SNTs data, their
aims and analytical methods. A two-phase systematic process resulted in inclusion and review of 35 publications.
Aims of the studies ranged from describing most popular nursing diagnoses, outcomes, and interventions on a unit to
predicting outcomes using multi-site data. Analytical techniques varied as well and included descriptive statistics,
correlations, data mining, and predictive modeling. The review underscored the value of developing a deep
understanding of the meaning and potential impact of nursing variables before merging with other sources of data.

Introduction

The main frontline providers of care are nurses who also represent the largest category of health workers in the
hospital setting. Among the 2.8 million registered nurses currently working in the United States (U.S.), 61% work in
hospitals1 whereas 19% of 297,1002 pharmacists and 41.9% of 854,698 physicians in practice work in hospitals.3,4

Nurses are responsible 24 hours each day for continuously identifying care issues, implementing and adjusting care
prescribed by themselves and other providers to achieve desired patient outcomes. To date, however, it has been
difficult to effectively evaluate the impact of nursing on patient outcomes. The growing use of electronic health records
(EHRs) to document care now offers the opportunity to use the data captured in practice for discovering knowledge
to transform health care. Thus, the documentation entered by nurses into EHRs, for the first time ever, is a potential
source for discovering the impact of nursing care on patient outcomes and using the knowledge to improve care. In
this article, we report our systematic review of studies that utilized nursing EHRs data to answer a variety of research
questions from describing nursing care for a specific population to predicting patient outcomes. The publications
reviewed provide a foundation for identifying future paths of inquiry involving nursing and other data retri

Standard Nursing Terminologies:
A Landscape Analysis

MBL Technologies, Clinovations,
Contract # GS35F0475X
Task Order # HHSP2332015004726

May 15, 2017

Identifying Challenges and Opportunities within Standard Nursing Terminologies 2

Table of Contents

I. Introduction …………………………………………………………………………………………. 4

II. Background ………………………………………………………………………………………….. 4

III. Landscape Analysis Approach ………………………………………………………………….. 6

IV. Summary of Background Data …………………………………………………………………. 7

V. Findings……………………………………………………………………………………………….. 8
A. Reference Terminologies ………………………………………………………………………………………..8

1. SNOMED CT ………………………………………………………………………………………………………………….. 8

2. Logical Observation Identifiers Names and Codes (LOINC) ……………………………………………….. 10

B. Interface Terminologies ………………………………………………………………………………………. 11

1. Clinical Care Classification (CCC) System ………………………………………………………………………… 11

2. International Classification for Nursing Practice (ICNP) ……………………………………………………. 12

3. NANDA International (NANDA-I) ……………………………………………………………………………………. 14

4.

5. Omaha System ……………………………………………………………………………………………………………. 16

6. Perioperative Nursing Data Set (PNDS) ………………………………………………………………………….. 18

7. Alternative Billing Concepts (ABC) Codes ……………………………………………………………………….. 19

C. Minimum Data Sets ……………………………………………………………………………………………. 20

1. Nursing Minimum Data Set (NMDS) ………………………………………………………………………………. 20

2. Nursing Management Minimum Data Set (NMMDS) ……………………………………………………….. 22

VI. Health IT Developers – Perspective …………………………………………………………. 23

VII. Emerging Issues in Using SNTs …………………………

o jni.o rg http://o jni.o rg/is s ues /?p=2852

The Hitchhiker ’s Guide to nursing informatics theory: using
the Data-Knowledge-Information-Wisdom framework to guide
informatics research

by Maxim To paz, PhD Student, RN, MA

Invited Guest Edito r

Citation

To paz, M. (2013). Invited Edito rial: T he Hitchhiker ’s Guide to nursing inf o rmatics theo ry: using the Data-
Kno wledge- Inf o rmatio n- Wisdo m f ramewo rk to guide inf o rmatics research. Online Journal of Nursing
Informatics (OJNI), 17 (3). Available at http://o jni.o rg/issues/?p=2852

Editorial
T heo ry is o ne o f the f undamental blo cks o f each scientif ic discipline. It is impo ssible to imagine bio lo gy
witho ut the theo ry o f Evo lutio n o r physics witho ut the theo ry o f Relativity. Nursing inf o rmatics, a relatively
new discipline, is also thirsty f o r its o wn theo ry. Ho wever, it is challenging to f ind literature that pro vides
clear theo retical guidance f o r nurse inf o maticians. In this co mmentary, I will brief ly o verview a theo retical
f ramewo rk that has high po tential to serve as o ne o f the f o undatio ns f o r nursing inf o rmatics. I will also
argue that to apply the described f ramewo rk, it needs to be merged with a nursing specif ic theo ry. I will
pro vide an example o f my dissertatio n wo rk to illustrate the necessary merge. T his co mmentary might be
used as a theo retical blueprint – o r the Hitchhiker ’s Guide- to guide nursing inf o rmatics research and
practice.

The Data-Inf ormation-Knowledge-Wisdom f ramework

Nursing inf o rmatics was created by the merge o f three well established scientif ic f ields: Inf o rmatio n
science, Co mputer science and Nursing science. One o f the mo st co mpelling def initio ns o f the discipline
states: “Nursing inf o rmatics science and practice integrates nursing, its inf o rmatio n and kno wledge and
their management with inf o rmatio n and co mmunicatio n techno lo gies to pro mo te the health o f peo ple,
f amilies and co mmunities wo rldwide” (Internatio nal Medical Inf o rmatics Asso ciatio n – Nursing Wo rking
Gro up, 2010). Unf o rtunately, very f ew attempts were made to generate a bro ad theo retical f ramewo rk f o r
nursing inf o rmatics. T here are several challenges to generate such f ramewo rk. First, the interdisciplinary
nature o f nursing inf o rmatics demands the use o f bro ad eno ugh theo retical f ramewo rk to enco mpass all
the disciplines. Also , the required theo retical f ramewo rk sho uld co nsider the practice/applicatio n do main;
the implementatio n o f nursing inf o rmatics in real healthcare settings. Recently, it was suggested that the
Data- Inf o rmatio n- Kno wledge- Wisdo m (DIKW) f ramewo rk has a high po tential to address these challenges
and this f ramewo rk was ado pted by the American Nurses Asso ciatio n (American Nurses Asso ci

Technological Forecasting & Social Change 126 (2018) 3–13

Contents lists available at ScienceDirect

Technological Forecasting & Social Change

Big data analytics: Understanding its capabilities and potential benefits
for healthcare organizations

Yichuan Wang a,⁎, LeeAnn Kung b, Terry Anthony Byrd a
a Raymond J. Harbert College of Business, Auburn University, 405 W. Magnolia Ave., Auburn, AL 36849, USA
b Rohrer College of Business, Rowan University, 201 Mullica Hill Road, Glassboro, NJ 08028, USA

⁎ Corresponding author.
E-mail addresses: [email protected] (Y. Wang), k

[email protected] (T.A. Byrd).

http://dx.doi.org/10.1016/j.techfore.2015.12.019
0040-1625/© 2016 Elsevier Inc. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:
Received 17 June 2015
Received in revised form 11 November 2015
Accepted 12 December 2015
Available online 26 February 2016

To date, health care industry has not fully grasped the potential benefits to be gained from big data analytics.
While the constantly growing body of academic research on big data analytics is mostly technology oriented, a
better understanding of the strategic implications of big data is urgently needed. To address this lack, this
study examines the historical development, architectural design and component functionalities of big data ana-
lytics. From content analysis of 26 big data implementation cases in healthcare, we were able to identify five big
data analytics capabilities: analytical capability for patterns of care, unstructured data analytical capability, deci-
sion support capability, predictive capability, and traceability.We alsomapped the benefits driven by big data an-
alytics in terms of information technology (IT) infrastructure, operational, organizational, managerial and
strategic areas. In addition, we recommend five strategies for healthcare organizations that are considering to
adopt big data analytics technologies. Our findingswill help healthcare organizations understand the big data an-
alytics capabilities and potential benefits and support them seeking to formulate more effective data-driven an-
alytics strategies.

© 2016 Elsevier Inc. All rights reserved.

Keywords:
Big data analytics
Big data analytics architecture
Big data analytics capabilities
Business value of information technology (IT)
Health care

1. Introduction

Information technology (IT)-related challenges such as inadequate
integration of healthcare systems and poor healthcare information
management are seriously hampering efforts to transform IT value to
business value in the U.S. healthcare sector (Bode

Use of a standardized nursing language for documentation of nursing care is vital both to the nursing profession and to the bedside/direct care nurse. The purpose of this article is to provide examples of the usefulness of standardized languages to direct care/bedside nurses. Currently, the American Nurses Association has approved thirteen standardized languages that support nursing practice, only ten of which are considered languages specific to nursing care. The purpose of this article is to offer a definition of standardized language in nursing, to describe how standardized nursing languages are applied in the clinical setting, and to explain the benefits of standardizing nursing languages. These benefits include: better communication among nurses and other health care providers, increased visibility of nursing interventions, improved patient care, enhanced data collection to evaluate nursing care outcomes, greater adherence to standards of care, and facilitated assessment of nursing competency. Implications of standardized language for nursing education, research, and administration are also presented.

Keywords: North American Nursing Diagnosis Association (NANDA); Nursing Intervention Classification (NIC); Nursing Outcome Classification (NOC); nursing judgments; patient care; quality care; standardized nursing language; communication

Citation: Rutherford, M., (Jan. 31, 2008) “Standardized Nursing Language: What Does It Mean for Nursing Practice? “OJIN: The Online Journal of Issues in Nursing. Vol. 13 No. 1.

Recently a visit was made by the author to the labor and delivery unit of a local community hospital to observe the nurses’ recent implementation of the Nursing Intervention Classification (NIC) (McCloskey-Dochterman & Bulechek, 2004) and the Nursing Outcome Classification (NOC) (Moorehead, Johnson, & Maas, 2004) systems for nursing care documentation within their electronic health care records system. �it is impossible for medicine, nursing, or any health care-related discipline to implement the use of [electronic documentation] without having a standardized language or vocabulary to describe key components of the care process. During the conversation, one nurse made a statement that was somewhat alarming, saying, “We document our care using standardized nursing languages but we don’t fully understand why we do.” The statement led the author to wonder how many practicing nurses might benefit from an article explaining how standardized nursing languages will improve patient care and play an important role in building a body of evidence-based outcomes for nursing.

Most articles in the nursing literature that reference standardized nursing languages are related to research or are scholarly discussions addressing the fine points surrounding the development or evaluation of these languages. Although the value of a specific, standardized nursing la